VA VB VC VD VE VF VG VH VI VJ VK VL VM VN VO VP VQ VR VS VT VU VV VW VX VY VZ

- var
- var computes the variance of the elements of an array regarding a given dimension.
- VaRauxdiagcat
- subroutine for VaRdiagtable.
- VaRauxsums
- subroutine for VaRpred (with option sums), calculates the transformation matrix.
- VaRcdfDG
- approximates the cumulative distribution function (CDF) for the class of quadratic forms of Gaussian vectors.
- VaRcgfDG
- computes the cumulant generating function (cgf) for the class of quadratic forms of Gaussian vectors.
- VaRcharfDG
- computes the characteristic function for the class of quadratic forms of Gaussian vectors.
- VaRcharfDGF2
- computes the Fourier transform of an approximating Gaussian cumulative distribution function (CDF) for the class of quadratic forms of Gaussian vectors.
- varcl
- Computes the variance of elements of a given interval bounds matrix (classified data)
- VaRcopula
- calculates the copula function, its derivatives and the inverse (in two dimensions).
- VaRcorrfDGF2
- computes the cumulative distribution function (CDF) of an approximated normal distribution for the class of quadratic forms of Gaussian vectors.
- VaRcredN
- Simulates a default distribution for a portfolio of homogeneous obligors where the default driver is normally distributed. Returns mean, variance and the quantile chosen.
- VaRcredN2
- Simulates a default distribution for a portfolio of obligors where the (joint) default driver is normally distributed. The dependence structure imposed corresponds to two homogeneous subportfolios driven by two default factors. Returns mean, variance and the quantile chosen.
- VaRcredTcop
- Simulates a default distribution for a portfolio of homogeneous obligors where individual default drivers are normally distributed. The joint distribution is generated by the use of a t-copula. Returns mean, variance and the quantile chosen.
- VaRcredTcop2
- Simulates a default distribution for a portfolio of obligors where the individual default driver is normally distributed. The dependence structure imposed corresponds to two homogeneous subportfolios driven by two default factors linked by a t-copula. Returns mean, variance and quantile chosen.
- VaRcumulantDG
- computes the n-th cumulant for the class of quadratic forms of Gaussian vectors.
- VaRcumulantsDG
- compute the first n cumulants for the class of quadratic forms of Gaussian vectors.
- VaRDGdecomp
- uses a generalized eigenvalue decomposition to do a suitable coordinate change. The new risk factors are independently standard normal distributed and the new Hessian matrix (Gamma) is diagonal.
- VaRDGdecompG
- computes the first and second derivatives with respect to the new risk factors.
- VaRdiagplot
- produces calibration and discrimination plots which verify the validity of a probability forecasts.
- VaRdiagtable
- produces table containing frequencies of predictive probabilities of the observations falling into specified intervals.
- VaRest
- estimates the value at risk (VaR).
- VaRestMC
- Partial Monte-Carlo method to calculate the Value at Risk (VaR) based on Delta-Gamma Approximation.
- VaRestMCcopula
- estimates VaR for a given portfolio using copulas
- varex
- an extended form of the var function - NaN and all values contained in excl are excluded from computation
- VaRfitcopula
- fits the copula to a given data
- VaRgrdiag
- produces calibration and discrimination plots which verify validity of probability forecasts.
- varimax
- performs a varimax rotation of loadings by maximizing the so-called varimax criterion
- varimaxval
- auxiliary quantlet for varimax, it calculates the value of the varimax negative criterion
- VaRmain
- sets defaults for library VaR.
- varml
- computes the maximum likelihood estimates of the model parameters (beta) and covariance (s) of residuals of a VAR(p) model without intercept
- VaRopt
- defines a list with optional parameters in VaR functions. The list is either created or new options are appended to an existing list.
- varorder
- standard selection criteria for Full VAR models
- VaRpred
- predicts the value at risk (VaR).
- VaRqDG
- computes the a-quantile for the class of quadratic forms of Gaussian vectors; uses Fourier inversion to approximate the cumulative distribution function (CDF).
- VaRqqplot
- visualizes the reliability of VaR forecasts.
- VaRRatMigCount
- Derives the matrix of migration counts from the matrix of migration events
- VaRRatMigRate
- computes the migration rates and the related estimated standard errors from the matrix of migration counts
- VaRRatMigRateM
- computes the m-period transition rates. Standard deviations of the transition rates are estimated by bootstrap.
- VaRsimcopula
- generates 2-dimensional random data from distribution with given copula
- VaRtest
- VaRtest tests all quantlets of the VaR library
- VaRtimeplot
- shows the time plot of VaR forecasts and the associated changes of the P&L of the portfolio.
- varunls
- computes the unconstrained least squares estimates of the model parameters (B), residuals (u), variance-covariance matrix of the residuals (s), and autocovariance matrix of the time series (g) of a K-dimensional VAR(p) model with/ without intercept
- VaRver
- verifies probability forecasts
- vec
- vec reshapes all given arguments into a vectors and concatenates them into a single vector which is returned.
- vec2mat
- stores the values of a vector into the upper triangle of a symmetric matrix regarding the sequence described in agglom
- volatility
- calculates the implied volatility of given options.
- volatilityaux
- auxiliary quantlet for volatility
- volsurf
- volsurf computes the implied volatility surface using a Kernel smoothing procedure. Either a Nadaraya-Watson estimator or a local polynomial regression is employed. Both are computed with a quartic Kernel. The metric is either moneyness, i.e. strike devided by the (implied) forward price of the und
- volsurfEBBS
- computes the implied volatility surface using a local polynomial estimation with an automatic bandwidth selection algorithm. The metric is either moneyness, i.e. strike devided by the (implied) forward price of the underlying, or the original strikes.
- volsurfplot
- produces a graphic visualising the implied volatility surface computed by the quantlet volsurf. The original options are shown as red points.
- volumes
- auxiliary quantlet for cartsplit, creates a vector of volumes: for each node of the tree "tr", calculates the volume of the rectangle corresponding to the node.

(C) MD*TECH Method and Data Technologies, 05.02.2006 | Impressum |